Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations591
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory50.8 KiB
Average record size in memory88.0 B

Variable types

Unsupported3
Numeric7

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
Calorias is highly overall correlated with Lipídeos and 1 other fieldsHigh correlation
Carboidrato is highly overall correlated with ColesterolHigh correlation
Colesterol is highly overall correlated with Carboidrato and 3 other fieldsHigh correlation
Lipídeos is highly overall correlated with Calorias and 4 other fieldsHigh correlation
Proteína is highly overall correlated with Colesterol and 2 other fieldsHigh correlation
Sódio is highly overall correlated with Colesterol and 2 other fieldsHigh correlation
Umidade is highly overall correlated with Calorias and 1 other fieldsHigh correlation
Numero is an unsupported type, check if it needs cleaning or further analysisUnsupported
Alimento is an unsupported type, check if it needs cleaning or further analysisUnsupported
Cálcio is an unsupported type, check if it needs cleaning or further analysisUnsupported
Umidade has 10 (1.7%) zerosZeros
Proteína has 31 (5.2%) zerosZeros
Lipídeos has 47 (8.0%) zerosZeros
Colesterol has 341 (57.7%) zerosZeros
Carboidrato has 154 (26.1%) zerosZeros
Sódio has 74 (12.5%) zerosZeros

Reproduction

Analysis started2024-11-06 06:50:28.056842
Analysis finished2024-11-06 06:50:32.636729
Duration4.58 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

Numero
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size9.2 KiB

Alimento
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size9.2 KiB

Umidade
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct579
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.341517
Minimum0
Maximum99.608667
Zeros10
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:32.716279image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.6986667
Q140.992833
median69.018
Q385.006667
95-th percentile93.835667
Maximum99.608667
Range99.608667
Interquartile range (IQR)44.013833

Descriptive statistics

Standard deviation30.222918
Coefficient of variation (CV)0.50930477
Kurtosis-0.79867031
Mean59.341517
Median Absolute Deviation (MAD)18.600333
Skewness-0.72331269
Sum35070.837
Variance913.42476
MonotonicityNot monotonic
2024-11-06T03:50:32.848717image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
1.7%
74.95133333 2
 
0.3%
15.82333333 2
 
0.3%
2.93 2
 
0.3%
68.72766667 1
 
0.2%
13.16475 1
 
0.2%
9.133333333 1
 
0.2%
3.216666667 1
 
0.2%
2.183333333 1
 
0.2%
2.733333333 1
 
0.2%
Other values (569) 569
96.3%
ValueCountFrequency (%)
0 10
1.7%
0.05 1
 
0.2%
0.12 1
 
0.2%
0.4133333333 1
 
0.2%
0.5966666667 1
 
0.2%
0.969 1
 
0.2%
1 1
 
0.2%
1.021666667 1
 
0.2%
1.103333333 1
 
0.2%
1.17 1
 
0.2%
ValueCountFrequency (%)
99.60866667 1
0.2%
99.37033333 1
0.2%
99.305 1
0.2%
97.372 1
0.2%
97.16866667 1
0.2%
96.78666667 1
0.2%
96.09333333 1
0.2%
95.87 1
0.2%
95.72833333 1
0.2%
95.69 1
0.2%

Calorias
Real number (ℝ)

HIGH CORRELATION 

Distinct328
Distinct (%)55.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195.47547
Minimum0
Maximum884
Zeros3
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:33.070200image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.5
Q157
median147
Q3300.5
95-th percentile502.5
Maximum884
Range884
Interquartile range (IQR)243.5

Descriptive statistics

Standard deviation170.35182
Coefficient of variation (CV)0.87147416
Kurtosis2.663445
Mean195.47547
Median Absolute Deviation (MAD)107
Skewness1.4262612
Sum115526
Variance29019.741
MonotonicityNot monotonic
2024-11-06T03:50:33.197422image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
884 8
 
1.4%
45 7
 
1.2%
36 7
 
1.2%
30 6
 
1.0%
29 6
 
1.0%
38 6
 
1.0%
13 6
 
1.0%
19 6
 
1.0%
41 6
 
1.0%
48 5
 
0.8%
Other values (318) 528
89.3%
ValueCountFrequency (%)
0 3
0.5%
1 1
 
0.2%
2 2
 
0.3%
8 1
 
0.2%
9 2
 
0.3%
10 1
 
0.2%
12 2
 
0.3%
13 6
1.0%
14 1
 
0.2%
15 2
 
0.3%
ValueCountFrequency (%)
884 8
1.4%
757 1
 
0.2%
725 1
 
0.2%
722 1
 
0.2%
696 1
 
0.2%
642 1
 
0.2%
620 1
 
0.2%
605 1
 
0.2%
596 1
 
0.2%
594 1
 
0.2%

Proteína
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct547
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.901003
Minimum0
Maximum36.45
Zeros31
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:33.319016image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.0841033
median5.64375
Q318.352083
95-th percentile30.18125
Maximum36.45
Range36.45
Interquartile range (IQR)17.26798

Descriptive statistics

Standard deviation10.310427
Coefficient of variation (CV)1.0413518
Kurtosis-0.53211267
Mean9.901003
Median Absolute Deviation (MAD)5.0640399
Skewness0.851216
Sum5851.4928
Variance106.30491
MonotonicityNot monotonic
2024-11-06T03:50:33.449143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
 
5.2%
0.32 2
 
0.3%
13.15625 2
 
0.3%
0.5652173913 2
 
0.3%
0.7666666667 2
 
0.3%
0.4041666667 2
 
0.3%
0.4083333333 2
 
0.3%
1.391304348 2
 
0.3%
0.4145833333 2
 
0.3%
2.133333333 2
 
0.3%
Other values (537) 542
91.7%
ValueCountFrequency (%)
0 31
5.2%
0.08958333333 1
 
0.2%
0.19375 1
 
0.2%
0.225 1
 
0.2%
0.2354166667 1
 
0.2%
0.2854166667 1
 
0.2%
0.2866666667 1
 
0.2%
0.3083333333 1
 
0.2%
0.3166666667 1
 
0.2%
0.32 2
 
0.3%
ValueCountFrequency (%)
36.45 1
0.2%
36.36458333 1
0.2%
36.03010024 1
0.2%
35.9 1
0.2%
35.88333333 1
0.2%
35.725 1
0.2%
35.68750024 1
0.2%
35.55361333 1
0.2%
35.06333333 1
0.2%
34.69 1
0.2%

Lipídeos
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct516
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1737416
Minimum0
Maximum100
Zeros47
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:33.580943image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.20716667
median2.294
Q311.9325
95-th percentile33.650167
Maximum100
Range100
Interquartile range (IQR)11.725333

Descriptive statistics

Standard deviation16.407895
Coefficient of variation (CV)1.7885718
Kurtosis14.10062
Mean9.1737416
Median Absolute Deviation (MAD)2.294
Skewness3.4351967
Sum5421.6813
Variance269.21902
MonotonicityNot monotonic
2024-11-06T03:50:33.711509image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47
 
8.0%
100 8
 
1.4%
0.1733333333 3
 
0.5%
0.22 3
 
0.5%
0.06 3
 
0.5%
0.1243333333 2
 
0.3%
0.07333333333 2
 
0.3%
0.06666666667 2
 
0.3%
0.1283333333 2
 
0.3%
0.3596666667 2
 
0.3%
Other values (506) 517
87.5%
ValueCountFrequency (%)
0 47
8.0%
0.05 1
 
0.2%
0.052 1
 
0.2%
0.05333333333 1
 
0.2%
0.06 3
 
0.5%
0.06366666667 1
 
0.2%
0.065 1
 
0.2%
0.06666666667 2
 
0.3%
0.06733333333 1
 
0.2%
0.069 1
 
0.2%
ValueCountFrequency (%)
100 8
1.4%
86.03933333 1
 
0.2%
82.361 1
 
0.2%
81.73366667 1
 
0.2%
67.43433333 1
 
0.2%
67.24566667 1
 
0.2%
67.097 1
 
0.2%
64.30866667 1
 
0.2%
63.459 1
 
0.2%
60.25666667 1
 
0.2%

Colesterol
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct249
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.616051
Minimum0
Maximum1272.372
Zeros341
Zeros (%)57.7%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:33.837187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q360.24
95-th percentile143.939
Maximum1272.372
Range1272.372
Interquartile range (IQR)60.24

Descriptive statistics

Standard deviation87.539776
Coefficient of variation (CV)2.2097047
Kurtosis73.88592
Mean39.616051
Median Absolute Deviation (MAD)0
Skewness6.6985909
Sum23413.086
Variance7663.2124
MonotonicityNot monotonic
2024-11-06T03:50:33.977631image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 341
57.7%
55.61 2
 
0.3%
50.3 2
 
0.3%
1.267333333 1
 
0.2%
73.204 1
 
0.2%
81.68733333 1
 
0.2%
1.350666667 1
 
0.2%
76.79766667 1
 
0.2%
63.20766667 1
 
0.2%
17.568 1
 
0.2%
Other values (239) 239
40.4%
ValueCountFrequency (%)
0 341
57.7%
1.267333333 1
 
0.2%
1.350666667 1
 
0.2%
1.85166 1
 
0.2%
2.112666667 1
 
0.2%
2.220333333 1
 
0.2%
3.331666667 1
 
0.2%
4.103333333 1
 
0.2%
4.742 1
 
0.2%
5.36975 1
 
0.2%
ValueCountFrequency (%)
1272.372 1
0.2%
601.47 1
0.2%
568 1
0.2%
516.2636667 1
0.2%
396.5716667 1
0.2%
392.883 1
0.2%
383.8253333 1
0.2%
355.94 1
0.2%
340.58 1
0.2%
315.3573333 1
0.2%

Carboidrato
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct438
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.101371
Minimum-0.045
Maximum99.61
Zeros154
Zeros (%)26.1%
Negative4
Negative (%)0.7%
Memory size9.2 KiB
2024-11-06T03:50:34.114068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-0.045
5-th percentile0
Q10
median7.7116667
Q323.4697
95-th percentile79.126117
Maximum99.61
Range99.655
Interquartile range (IQR)23.4697

Descriptive statistics

Standard deviation25.86898
Coefficient of variation (CV)1.3542997
Kurtosis0.93780918
Mean19.101371
Median Absolute Deviation (MAD)7.7116667
Skewness1.4865861
Sum11288.91
Variance669.20411
MonotonicityNot monotonic
2024-11-06T03:50:34.251391image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 154
 
26.1%
54.73042657 1
 
0.2%
66.63564058 1
 
0.2%
18.36386616 1
 
0.2%
25.80975 1
 
0.2%
77.45071413 1
 
0.2%
16.49525 1
 
0.2%
61.47916667 1
 
0.2%
14.00516667 1
 
0.2%
58.75246377 1
 
0.2%
Other values (428) 428
72.4%
ValueCountFrequency (%)
-0.045 1
 
0.2%
-0.02666666667 1
 
0.2%
-0.02333333333 1
 
0.2%
-0.006666666667 1
 
0.2%
0 154
26.1%
0.02 1
 
0.2%
0.05833333333 1
 
0.2%
0.06329999256 1
 
0.2%
0.23625 1
 
0.2%
0.3913333333 1
 
0.2%
ValueCountFrequency (%)
99.61 1
0.2%
99.54 1
0.2%
94.45 1
0.2%
91.17666667 1
0.2%
90.79241667 1
0.2%
89.33666667 1
0.2%
89.22333333 1
0.2%
89.19416667 1
0.2%
88.84057971 1
0.2%
87.89898551 1
0.2%

Cálcio
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size9.2 KiB

Sódio
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct516
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean469.48503
Minimum0
Maximum39943.203
Zeros74
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2024-11-06T03:50:34.378001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.8883333
median38.783333
Q3120.01867
95-th percentile1193.9447
Maximum39943.203
Range39943.203
Interquartile range (IQR)118.13033

Descriptive statistics

Standard deviation2765.1421
Coefficient of variation (CV)5.8897343
Kurtosis121.61439
Mean469.48503
Median Absolute Deviation (MAD)37.801333
Skewness10.51614
Sum277465.65
Variance7646010.8
MonotonicityNot monotonic
2024-11-06T03:50:34.513378image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 74
 
12.5%
114.9053333 2
 
0.3%
3.333333333 2
 
0.3%
27.58666667 1
 
0.2%
1.244666667 1
 
0.2%
0.5688333333 1
 
0.2%
4.626666667 1
 
0.2%
352.0266667 1
 
0.2%
239.2 1
 
0.2%
229.8166667 1
 
0.2%
Other values (506) 506
85.6%
ValueCountFrequency (%)
0 74
12.5%
0.3553333333 1
 
0.2%
0.5006666667 1
 
0.2%
0.5203333333 1
 
0.2%
0.5513333333 1
 
0.2%
0.5688333333 1
 
0.2%
0.5913333333 1
 
0.2%
0.5966666667 1
 
0.2%
0.6253333333 1
 
0.2%
0.629 1
 
0.2%
ValueCountFrequency (%)
39943.203 1
0.2%
32560 1
0.2%
23431.52167 1
0.2%
22299.90033 1
0.2%
22179.66667 1
0.2%
13585.05667 1
0.2%
10052.41133 1
0.2%
5875.029 1
0.2%
5024.208333 1
0.2%
4439.55 1
0.2%

Interactions

2024-11-06T03:50:31.771874image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.157157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.753698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.332318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.027999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.602537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.199192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.859123image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.244379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.833453image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.418561image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.107488image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.683106image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.278629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.942790image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.322233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.907922image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.500702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.184716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.762637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.355021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:32.038626image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.411791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.999328image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.589309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.271783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.849522image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.439764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:32.124381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.492790image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.079994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.674650image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.348835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.934432image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.519765image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:32.217574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.578765image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.163331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.761292image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.431645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.020488image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.602233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:32.303585image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:28.660896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.243207image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:29.931593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:30.510518image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.103313image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-06T03:50:31.681596image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-06T03:50:34.605436image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
CaloriasCarboidratoColesterolLipídeosProteínaSódioUmidade
Calorias1.0000.2360.3020.7240.4340.411-0.938
Carboidrato0.2361.000-0.602-0.254-0.378-0.182-0.307
Colesterol0.302-0.6021.0000.5770.7390.567-0.203
Lipídeos0.724-0.2540.5771.0000.6090.551-0.591
Proteína0.434-0.3780.7390.6091.0000.538-0.366
Sódio0.411-0.1820.5670.5510.5381.000-0.395
Umidade-0.938-0.307-0.203-0.591-0.366-0.3951.000

Missing values

2024-11-06T03:50:32.431868image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-06T03:50:32.578082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

NumeroAlimentoUmidadeCaloriasProteínaLipídeosColesterolCarboidratoCálcioSódio
01Arroz, integral, cozido70.1386671232.5882501.0003330.025.8097505.2041.244667
10Arroz, integral, cru12.1798333597.3232861.8648330.077.4507147.8181.645667
20Arroz, tipo 1, cozido69.1136671282.5208170.2270000.028.0598503.5443331.200667
30Arroz, tipo 1, cru13.2245003577.1585400.3350000.078.7595434.4143331.019167
40Arroz, tipo 2, cozido68.7276671302.5684170.3616670.028.1925833.3336671.959667
50Arroz, tipo 2, cru13.1647503587.2418830.2755000.078.8814504.83350.568833
60Aveia, flocos, crua9.13333339313.9210268.4966670.066.63564147.894.626667
70Biscoito, doce, maisena3.2166674428.07252211.9666670.075.23414554.45352.026667
80Biscoito, doce, recheado com chocolate2.1833334716.39721719.5833330.070.54944927.23239.200000
90Biscoito, doce, recheado com morango2.7333334715.71982619.5733330.071.01350735.78229.816667
NumeroAlimentoUmidadeCaloriasProteínaLipídeosColesterolCarboidratoCálcioSódio
5860Amêndoa, torrada, salgada3.10600058018.55475947.3243330.029.547240236.704333278.522667
5870Castanha-de-caju, torrada, salgada3.46400057018.50936746.2796670.029.13496632.587667125.000000
5880Castanha-do-Brasil, crua3.52400064214.53634063.4590000.015.078660146.3366670.654000
5890Coco, cru42.9611674063.69183441.9763330.010.4016666.484515.320000
5910Farinha, de mesocarpo de babaçu, crua15.8233333281.4062670.1980000.079.17306760.95233312.463000
5920Gergelim, semente3.85933358321.16466750.4326670.021.61766600.000000
5930Linhaça, semente6.68300049514.08386732.2529330.043.312199211.4976678.673333
5940Pinhão, cozido50.5133331742.9803670.7470000.043.91763315.7673330.862667
5950Pupunha, cozida54.4600002182.52291712.7616670.029.56941727.5863330.908667
5960Noz, crua6.24466762013.97080159.3596670.018.363866105.3063334.570667

Duplicate rows

Most frequently occurring

UmidadeCaloriasProteínaLipídeosColesterolCarboidratoSódio# duplicates
00.08840.0100.00.00.00.08